Zobrazeno 1 - 6
of 6
pro vyhledávání: '"Venkata Joopudi"'
Autor:
Jennifer J, Liang, Ching-Huei, Tsou, Bharath, Dandala, Ananya, Poddar, Venkata, Joopudi, Diwakar, Mahajan, John, Prager, Preethi, Raghavan, Michele, Payne
Publikováno v:
AMIA Annu Symp Proc
Overabundance of information within electronic health records (EHRs) has resulted in a need for automated systems to mitigate the cognitive burden on physicians utilizing today’s EHR systems. We present ProSPER, a Problem-oriented Summary of the Pa
Publikováno v:
Drug Safety. 42:135-146
Adverse drug events (ADEs) occur in approximately 2–5% of hospitalized patients, often resulting in poor outcomes or even death. Extraction of ADEs from clinical narratives can accelerate and automate pharmacovigilance. Using state-of-the-art deep-
Autor:
Ching-Huei Tsou, Parthasarathy Suryanarayanan, Bharath Dandala, Jennifer J. Liang, Venkata Joopudi
Publikováno v:
JMIR Medical Informatics
JMIR Medical Informatics, Vol 8, Iss 7, p e18417 (2020)
JMIR Medical Informatics, Vol 8, Iss 7, p e18417 (2020)
Background An adverse drug event (ADE) is commonly defined as “an injury resulting from medical intervention related to a drug.” Providing information related to ADEs and alerting caregivers at the point of care can reduce the risk of prescriptio
Autor:
Parthasarathy Suryanarayanan, Jennifer Liang, Venkata Joopudi, Ching-Huei Tsou, Bharath Dandala
BACKGROUND An adverse drug event (ADE) is commonly defined as “an injury resulting from medical intervention related to a drug.” Providing information related to ADEs and alerting caregivers at the point of care can reduce the risk of prescriptio
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::237dd10426bde63738e1fdebc1796de5
https://doi.org/10.2196/preprints.18417
https://doi.org/10.2196/preprints.18417
Publikováno v:
Journal of biomedical informatics. 86
Abbreviations sense disambiguation is a special case of word sense disambiguation. Machine learning methods based on neural networks showed promising results for word sense disambiguation (Festag and Spreckelsen, 2017) [1] and, here we assess their e
Chemically Augmented String Kernel for Extraction and Classification of Chemical Compounds from Text
Autor:
Akansha Singh, Venkata Joopudi, Anirudh Murali, Priya Gandhi, Utkarsha Prakash, Keerthana Kumar
Publikováno v:
K-CAP
Chemical compounds provide key information for text documents in the material science domain. For extraction and classification of chemical compounds in text, we present a novel kernel - Chemically Augmented String Kernel (CASK) - which incorporates